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debbiesoon/
summarise_v8

Name: summarise_v8
Rating: 2.5 (10 reviews)

generated_from_trainer

apache-2.0

endpoints_compatible

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SGH logo.png

This model is a fine-tuned version of allenai/led-base-16384 on the SGH news articles and summaries dataset. It achieves the following results on the evaluation set:

Loss: 0.8163
Rouge2 Precision: 0.3628
Rouge2 Recall: 0.3589
Rouge2 Fmeasure: 0.3316

Model description

This model was created to generate summaries of news articles.

Intended uses & limitations

The model takes up to maximum article length of 768 tokens and generates a summary of maximum length of 512 tokens, and minimum length of 100 tokens.

Training and evaluation data

This model was trained on 100+ articles and summaries from SGH.

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge2 Precision	Rouge2 Recall	Rouge2 Fmeasure
1.5952	0.23	10	1.0414	0.2823	0.3908	0.3013
1.8116	0.47	20	0.9171	0.3728	0.273	0.3056
1.6289	0.7	30	0.8553	0.3284	0.2892	0.291
1.5074	0.93	40	0.8163	0.3628	0.3589	0.3316

Framework versions

Transformers 4.21.3
Pytorch 1.12.1+cu113
Datasets 1.2.1
Tokenizers 0.12.1

debbiesoon/summarise_v8